# Random variables in Julia (working list)

**URL:** https://discourse.julialang.org/t/random-variables-in-julia-working-list/48762
**Category:** Statistics
**Tags:** distributions
**Created:** [October 21, 2020, 5:18pm UTC](https://discourse.julialang.org/t/random-variables-in-julia-working-list/48762 "2020-10-21T17:18:20Z")
**Posts on this page:** 1
**Showing post:** 29

<div class="post-metadata">

### Author: ![Albert\_Zevelev](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/albert_zevelev/32/11844_2.png) [@Albert\_Zevelev](https://discourse.julialang.org/u/Albert_Zevelev)
#### Post date: [November 8, 2022, 1:34am UTC](https://discourse.julialang.org/t/random-variables-in-julia-working-list/48762/29 "2022-11-08T01:34:13Z")

</div>

One of the nice features of [Distributions](https://github.com/JuliaStats/Distributions.jl).jl is the ability to create new transformed distributions from existing distributions.

- `MixtureModel([Normal(0,1),Cauchy(0,1)], [0.5,0.5])` returns a new random variable

- `Truncated(Cauchy(0,1), 0.25, 1.8)`

- `convolve(Cauchy(0,1), Cauchy(5,2))`

A recent PR proposes [folded distributions](https://github.com/JuliaStats/Distributions.jl/pull/1631).  
This is cool b/c it automatically allows the user to access a large number of distributions:  
folded-Cauchy/folded-normal/Half-Cauchy/half-logistic/half-normal etc

There has been discussion about a generic ZeroInflated distribution [here](https://github.com/JuliaStats/Distributions.jl/pull/1393), [here](https://discourse.julialang.org/t/truncated-poisson-distribution-probs-not-adding-up-to-one/61053), [here](https://github.com/JuliaStats/Distributions.jl/pull/390)

Are there other important transformations of random variables not considered yet?  
Maybe [CensoredDistribution](https://reference.wolfram.com/language/ref/CensoredDistribution.html), [Conditioned](https://reference.wolfram.com/language/ref/Conditioned.html) & [Derived Statistical Distributions](https://reference.wolfram.com/language/guide/DerivedDistributions.html) can provide some inspiration?

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